{"id":22668454,"url":"https://github.com/lanl/sepia","last_synced_at":"2025-08-25T08:19:38.144Z","repository":{"id":47305570,"uuid":"267692609","full_name":"lanl/SEPIA","owner":"lanl","description":"Simulation-Enabled Prediction, Inference, and Analysis: physics-informed statistical learning. ","archived":false,"fork":false,"pushed_at":"2023-10-02T21:11:49.000Z","size":218537,"stargazers_count":35,"open_issues_count":22,"forks_count":7,"subscribers_count":8,"default_branch":"master","last_synced_at":"2025-07-31T12:29:40.651Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/lanl.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"License-BSD-3","code_of_conduct":null,"threat_model":null,"audit":null,"citation":"CITATION.cff","codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2020-05-28T20:43:51.000Z","updated_at":"2025-03-17T12:02:26.000Z","dependencies_parsed_at":"2022-09-06T14:02:00.427Z","dependency_job_id":"bfa9a5df-66da-46da-b653-dff50454a4f1","html_url":"https://github.com/lanl/SEPIA","commit_stats":null,"previous_names":[],"tags_count":3,"template":false,"template_full_name":null,"purl":"pkg:github/lanl/SEPIA","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lanl%2FSEPIA","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lanl%2FSEPIA/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lanl%2FSEPIA/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lanl%2FSEPIA/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/lanl","download_url":"https://codeload.github.com/lanl/SEPIA/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lanl%2FSEPIA/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":272031550,"owners_count":24861688,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-08-25T02:00:12.092Z","response_time":1107,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-12-09T15:15:15.895Z","updated_at":"2025-08-25T08:19:38.085Z","avatar_url":"https://github.com/lanl.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# SEPIA\n[![SEPIA-CI Status][ci-status-img]](https://github.com/lanl/SEPIA/actions)\n\nSimulation-Enabled Prediction, Inference, and Analysis: physics-informed statistical learning.\nThis is a Python adaptation of [GPMSA](https://github.com/lanl/gpmsa).\n\n\u003ca href=\"https://zenodo.org/badge/latestdoi/267692609\"\u003e\u003cimg src=\"https://zenodo.org/badge/267692609.svg\" alt=\"DOI\"\u003e\u003c/a\u003e\n\n\u003cimg src=\"docs/sepia.png\" alt=\"sepia cuttlefish logo by Natalie Klein\" width=\"150\"/\u003e\n\n### What to Expect\nSEPIA is intended to be a tool that enhances the collaboration between statisticians\nand domain scientists who are using computational models to augment observations in\nR\u0026D and engineering applications. The code and the methodology \nit implements can be demonstrated simply, but new R\u0026D often raises issues in \nanalysis that are subtle and complicated. SEPIA has many options to address issues \nthat have come up in the development team's experience in scientific applications,\nand it is available to be extended to address new application requirements. We \nrecommend the domain scientist consult or partner with a statistician familiar with the\nmethodology to ensure best outcomes. \n\n### Documentation\nCurrent documentation is at [Read the Docs](http://sepia-lanl.readthedocs.io).\nThe documentation contains a workflow guide that is helpful for new users to read, and also contains a quick reference for basic commands as well as an API.\n\n### Examples\nBasic usage is demonstrated in the Examples directory. \nAfter looking at the documentation, check out the examples.\n\n### Install package \nFor cleaner package management and to avoid conflicts between different versions of packages,\nwe recommend installing inside an Anaconda or pip environment.\nHowever, this is not required.\n\nFirst, pull down the current source code from either by downloading a zip file or using `git clone`.\n\nFrom the command line, while in the main SEPIA directory, use the following command to install sepia::\n\n        pip install -e .[sepia]\n\nThe `-e` flag signals developer mode, meaning that if you update the code from Github, your installation will automatically\ntake those changes into account without requiring re-installation. Note: this command may not work properly with all shells; it has been tested with `bash`.\nSome other essential packages used in SEPIA may be installed if they do not exist in your system or environment.\n\nIf you encounter problems with the above install method, you may try to install dependencies manually before installing SEPIA.\nFirst, ensure you have a recent version of Python (greater than 3.5).\nThen, install packages `numpy`, `scipy`, `pandas`, `matplotlib`, `seaborn`, `statsmodels`, and `tqdm`.        \n\n### Citing Sepia\nUsing Sepia in your work? Cite as:\n\nJames Gattiker, Natalie Klein, Earl Lawrence, \u0026 Grant Hutchings.\nlanl/SEPIA. Zenodo. https://doi.org/10.5281/zenodo.4048801 \n\n\n---\n\nApproved by LANL/NNSA for software release: C19159 SEPIA \n\n© 2020. Triad National Security, LLC. All rights reserved.\nThis program was produced under U.S. Government contract 89233218CNA000001 for Los Alamos\nNational Laboratory (LANL), which is operated by Triad National Security, LLC for the U.S.\nDepartment of Energy/National Nuclear Security Administration. All rights in the program are\nreserved by Triad National Security, LLC, and the U.S. Department of Energy/National Nuclear\nSecurity Administration. The Government is granted for itself and others acting on its behalf a\nnonexclusive, paid-up, irrevocable worldwide license in this material to reproduce, prepare\nderivative works, distribute copies to the public, perform publicly and display publicly, and to permit\nothers to do so.\n\nThis program is open source under the BSD-3 License.\nRedistribution and use in source and binary forms, with or without modification, are permitted\nprovided that the following conditions are met:\n1. Redistributions of source code must retain the above copyright notice, this list of conditions and\nthe following disclaimer. \n2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions\nand the following disclaimer in the documentation and/or other materials provided with the\ndistribution. \n3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse\nor promote products derived from this software without specific prior written permission.\n\nTHIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS\nIS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\nIMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR\nPURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR\nCONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\nEXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\nPROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;\nOR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,\nWHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR\nOTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF\nADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\n\n[ci-status-img]: https://github.com/lanl/SEPIA/workflows/SEPIA-CI/badge.svg\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flanl%2Fsepia","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flanl%2Fsepia","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flanl%2Fsepia/lists"}